Practical Statistics 2022 for Data Science with Python and R
What you'll learn
- Data Analysis
- Business Analytics
- Regression Analysis
- Descriptive Statistics
- Inferential Statistics
- Hypothesis Testing
- Chi Square Test
- Linear Regression
- Logistic Regression
- Machine Learning
- Data Science
- Knowledge Of Basic Python and R
- Motivation to Learn
Data Science and Analytics is a highly rewarding career that allows you to solve some of the world’s most interesting problems and Statistics the base for all the analysis and Machine Learning models. This makes statistics a necessary part of the learning curve. Analytics without Statistics is baseless and can anytime go in the wrong direction.
For a majority of Analytics professionals and Beginners, Statistics comes as the most intimidating, doubtful topic, which is the reason why we have created this course for those looking forward to learn Statistics and apply various statistical methods for analysis with the most elaborate explanations and examples!
This course is made to give you all the required knowledge at the beginning of your journey, so that you don’t have to go back and look at the topics again at any other place. This course is the ultimate destination with all the knowledge, tips and trick you would require to start your career.
This course provides Full-fledged knowledge of Statistics, we cover it all.
Our exotic journey will include the concepts of:
1. What’s and Why’s of Statistics – Understanding the need for Statistics, difference between Population and Samples, various Sampling Techniques.
2. Descriptive Statistics will include the Measures Of central tendency - Mean, Median, Mode and the Measures of Variability - Variance, SD, IQR, Bessel’s Correction
3. Further you will learn about the Shapes Of distribution - Bell Curve, Kurtosis, Skewness.
4. You will learn about various types of variables, their interactions like Correlation, Covariance, Collinearity, Multicollinearity, feature creation and selection.
5. As part of Inferential statistics, you will learn various Estimation Techniques, Properties of Normal Curve, Central Limit Theorem calculation and representation of Z Score and Confidence Intervals.
6. In Hypothesis Testing you will learn how to formulate a Null Hypothesis and the corresponding Alternate Hypothesis.
7. You will learn how to choose and perform various hypothesis tests like Z – test, One Sample T Test, Independent T Test, Paired T Test, Chi Square – Goodness Of Fit, Chi-Square Test for Independence, ANOVA
8. In regression Analysis you will learn about end-to-end variable creation selection data transformation, model building and Evaluation process for both Linear and Logistic Regression.
9. In-depth explanation for Statistical Methods with all the real-life tips and tricks to give you an edge from someone who has just the introductory knowledge which is usually not provided in a beginner course.
10. All explanations provided in a simple language to make it easy to understand and work on in future.
11. Hands-on practice on more than 15 different Datasets to give you a quick start and learning advantage of working on different datasets and problems.
Who this course is for:
I have done B.tech in Computer Science Engineering and 10 + years of experience as a professional instructor and trainer for Data Science and programming. During the course of my career I have developed a skill set in analyzing data and I love sharing my knowledge to help other people learn the power of programming, the ability to analyze data, as well as present the data in clear and beautiful visualizations.
I am a Data Scientist and have experience in python, Deep learning, NLP and Big Data. I provide in-person data science, Machine Learning and Deep Learning training to Data science enthusiasts with 0 to 30+ years of Experience. I believe in learning by doing, hence all of my courses will give an in-depth knowledge of concepts followed by detailed explanations of codes, tips and tricks which I have learnt over years. The sample problems and examples will allow you to explore more and give you enough practice to gain confidence at each and every concept. I am here to help you stay on the cutting edge of Data Science and Technology.
To sum up, I am absolutely and utterly passionate about Data Science and I am looking forward to sharing my passion and knowledge with you!